Yan Yan

Computer Vision and Pattern Recognition · with Shang · 2021–2024

A researcher in the Science corpus: 3 papers; trusts 150 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 86 citations into it
• Artificial Intelligence — 75 citations into it
• Generative Models — 22 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Yan Yan trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Yoshua Bengio
5. Diederik P. Kingma
6. Yann LeCun
7. Jia Deng
8. Ross B. Girshick
9. Ilya Sutskever
10. Karen Simonyan

Papers from Yan Yan's perspective

Ordered by how strongly the researchers Yan Yan trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. ImageNet: A large-scale hierarchical image database
4. Learning Multiple Layers of Features from Tiny Images
5. Attention is All you Need (Neural Information Processing Systems)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Post-Training Quantization on Diffusion Models (2022) — 336 citations
• LLaVA-Prumerge: Adaptive Token Reduction for Efficient Large Multimodal Models (2024) — 376 citations
• Lipschitz Continuity Guided Knowledge Distillation (2021) — 31 citations